Field
The subject matter disclosed herein relates to positioning systems.
Information
A satellite positioning system (SPS), such as the Global Positioning System (GPS), Galileo, and Glonass, for example, typically provides position, velocity, and/or time information. In a particular implementation, an SPS may comprise an GNSS (Global Navigation Satellite System). A variety of receivers have been designed to decode signals transmitted from satellite vehicles (SV) of an SPS to determine position, velocity, and/or time. In general, to decipher such signals and compute a final position, a receiver may first acquire signals from SVs that are in view, measure and track the received signals, and recover navigational data from the signals. By accurately measuring distances or “pseudoranges” to multiple SVs, a receiver may triangulate its position, e.g., solving for a latitude, longitude, and/or altitude. In particular, the receiver may measure distance by measuring the time that signals take to travel from a respective SV to the receiver.
In certain locations, such as urban environments with tall buildings, a receiver may only be able to acquire signals from three or less SVs. In such situations, the receiver may be unable to resolve all four variables of a position solution that include latitude, longitude, altitude, and time. If signals from fewer than four SVs are available, the receiver may be unable to calculate its position based on an SPS alone. To address such a limitation, receivers may employ hybrid location technology that involves signals from base stations of a wireless communication system, for example. As with SV signals, hybrid receivers may measure time delays of wireless signals to measure distances to base stations of a network. Hybrid receivers may utilize signals from base stations as well as any acquired signals from SVs of an SPS, to resolve position and time variables. Such a hybrid positioning technique may allow a receiver to compute a position solution in a wide variety of locations where SPS-only positioning techniques may fail. In code division multiple access (CDMA) mobile wireless systems, for example, a base station measurement portion of a hybrid technique may include techniques such as Advanced Forward Link Trilateration (AFLT).
Accuracy of a position solution determined by a receiver may be affected by the degree of time precision within a positioning system. In synchronized systems, such as existing CDMA systems for example, timing information communicated by cellular base stations may be synchronized with timing information from SVs of an SPS, providing precise time throughout the system. In some systems, such as the Global System for Mobile Communications (GSM), timing information may not be synchronized between base stations and signals transmitted by SVs of an SPS. In such systems, Location Measurement Units (LMUs) may be added to an existing infrastructure to provide precise timing information for a wireless network.
A technique that may be used in position determining systems involves the use of Kalman filters. A Kalman filter (KF) may comprise a recursive data estimation algorithm for modeling attributes or states of moving entities such as aircraft, people, and vehicles, just to name a few examples. Such attributes or states may include velocity and/or position. A current state of a system and a current measurement may be used to estimate a new state of the system. A Kalman filter may combine available measurement data, prior knowledge about a system, measuring devices, and/or error statistics to produce an estimate of desired variables in such a manner that the error may be statistically minimized.